Bibliographic record
Abstract
This paper discusses the cognitive process (es) in recognizing instances of genre and the effects of generic features have on recognition of genre. Following the ESP tradition, the paper takes the communicative purpose as the defining feature of a genre and follow Martin’s stratified model of language and context in for the analysis. Based on a preliminary study conducted among three geologists, this paper proposes a model revealing the cognitive process (es) in recognition of instances of genre. According to the model, the cognitive recognition of a genre basically goes from the bottom up, and the effects that the generic features have on recognition of instances of genres decrease from the top down. However, as the cognitive processes are very complicated, the top-down and bottom-up processes may sometimes interweave. Even at each stratum alone, the reader may have to experience a complicated interactive process. The schema theory is an important theory that works as a general thread throughout the model proposed. Apart from the general schema-matching processes at the beginning and the end of the whole processes, there might exist a schema-matching process at each processing stratum, too.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".